System Requirements:
Windows 11 24H2
Python (code developed using 3.12.4)

Installation:
https://www.python.org/downloads/

To install the required packages, open command prompt and use the following commands:
pip install pandas
pip install matplotlib
pip install scikit-learn
pip install scipy

Keep all Python code in the same folder.

Install time may vary based on internet connection speed.

Instructions:
Demo Data Included = Demo_DFFO_Data.csv
1.) Create folders called "input_folder" and "output_folder" in the same path with the Python code.
2.) Update the "input_folder", "output_folder", and "udf_path" variables in process_data_wrap.py to the same path with the Python code and save.
3.) Organize a .csv input file as follows:
	Row 1 = column titles (Event Name, Start Time, Stop Time, Time, DF/F0)
	Column 1 = Names for target events
	Column 2 = Start timestamp for events
	Column 3 = Stop timestamp for events
	Column 4 = Timestamps from photometry recording
	Column 5 = DF/F0 trace
4.) Place .csv input files into the input_folder.
5.) Double-click process_data_wrap.py or type process_data_wrap.py into command prompt and press enter to run.

Output:
The output_folder will contain the following .csv files: trace quantificactions, event z-score traces, and event DF/F0 traces. Subfolders will contain plots of event traces. Run time is ~1.25 minutes depending on recording length, sampling rate, and number of behaviors.